The objective of cross-view image geo-localization is to find the best matched aerial-view image (with GPS information) in a reference dataset for a query street-view image. We conduct the experiment on CVUSA [1]}, which is the most popular benchmark for this problem containing 35,532 training pairs and 8,884 test pairs. Each pair consists of a query street image and the corresponding orientation-aligned aerial image at the same GPS location. For example, as shown in Fig. REF , the left two images (street-view panorama and aerial-view images) are the original aligned image pair and the yellow line denotes the \(0^{\circ }\)  which corresponds to the South direction (\(180^{\circ }\)  corresponds to the North direction). We use \([0,360]^{\circ }\)  to denote different angles as marked on those two images.
